Instructions to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hf-transformers-bot HF Staff
Upload tiny models for RobertaPreLayerNormForTokenClassification
eb5e50e Download pytorch_model.bin from hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 369 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification/resolve/main/pytorch_model.bin
- Command line
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hf download hf://hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-RobertaPreLayerNormForTokenClassification/resolve/main/pytorch_model.bin
369 kB
- Xet hash:
- 7e1b378883fbb1f60c269dd8728fd62619df77a76ba05a9a396f3f292dc4c5b0
- Size of remote file:
- 369 kB
- SHA256:
- 02d22a082dd85173cab54c61c7aba631b0c858c5d578ae42baca42de5614d490
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